Scott Alfeld
Impact in
- Artificial Intelligence top 10%
- Adversarial Robustness in Machine Learning
- Privacy-Preserving Technologies in Data
- Anomaly Detection Techniques and Applications
- Internet Traffic Analysis and Secure E-voting
- Signal Processing top 10%
- Advanced Malware Detection Techniques
Papers in
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- Adversarial Robustness in Machine Learning 6
- Anomaly Detection Techniques and Applications 2
- Internet Traffic Analysis and Secure E-voting 2
- Privacy-Preserving Technologies in Data 2
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- Privacy, Security, and Data Protection 2
- Co-authors
- Paul Barford (6 shared papers)Xiaojin Zhu (3 shared papers)S. Muthukrishnan (2 shared papers)Benjamin I. P. Rubinstein (2 shared papers)Zhifeng Kong (1 shared paper)Carol Barford (1 shared paper)Yevgeniy Vorobeychik (4 shared papers)M. Hunter Lanier (1 shared paper)
- Journals
- ACM Transactions on Knowledge Discovery from Data (1 paper)Lecture notes in computer science (1 paper)Frontiers in artificial intelligence and applications (1 paper)2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (1 paper)SSRN Electronic Journal (1 paper)
- Partner nations
- United StatesAustraliaNetherlands
In The Last Decade
Scott Alfeld
14 papers receiving 257 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 189
- Signal Processing 54
- Computer Science Applications 22
- Health Informatics 4
- Computer Networks and Communications 53
Countries citing papers authored by Scott Alfeld
This map shows the geographic impact of Scott Alfeld's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Scott Alfeld with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Alfeld more than expected).
Fields of papers citing papers by Scott Alfeld
This network shows the impact of papers produced by Scott Alfeld. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Scott Alfeld. The network helps show where Scott Alfeld may publish in the future.
Co-authors
The 18 scholars most cited alongside Scott Alfeld, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 126 | |
| 2 | 2016 | 63 | |
| 3 | 2022 | 40 | |
| 4 | 2017 | 19 | |
| 5 | 2012 | 4 | |
| 6 | 2018 | 3 | |
| 7 | 2023 | 2 | |
| 8 | 2019 | 2 | |
| 9 | 2018 | 2 | |
| 10 | Adversarial Regression with Multiple Learners | 2018 | 1 |
| 11 | 2023 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2021 | 1 | |
| 14 | 2014 | 1 | |
| 15 | 2024 | 0 | |
| 16 | 2016 | 0 |
About Scott Alfeld
Scott Alfeld is a scholar working on Artificial Intelligence, Sociology and Political Science, Information Systems, Computer Networks and Communications and Statistical and Nonlinear Physics, having authored 16 papers that have together received 266 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (6 papers), Spam and Phishing Detection (3 papers), Anomaly Detection Techniques and Applications (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Privacy-Preserving Technologies in Data (2 papers), Privacy, Security, and Data Protection (2 papers), Electric Power System Optimization (2 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (189 citations), Signal Processing (54 citations), Computer Science Applications (22 citations), Health Informatics (4 citations) and Computer Networks and Communications (53 citations). Scott Alfeld has collaborated with scholars based in United States, Australia and Netherlands. Frequent co-authors include Paul Barford, Xiaojin Zhu, S. Muthukrishnan, Benjamin I. P. Rubinstein, Zhifeng Kong, Carol Barford, Yevgeniy Vorobeychik, M. Hunter Lanier, Nathan Jacobs and Tina Eliassi‐Rad. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, Lecture notes in computer science, Frontiers in artificial intelligence and applications, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) and SSRN Electronic Journal.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.